Liquid AI: LFM2.5-1.2B-Instruct
liquid/lfm-2.5-1.2b-instruct:free
Access LFM2.5-1.2B-Instruct from Liquid AI using Puter.js AI API.
Get Started// npm install @heyputer/puter.js
import { puter } from '@heyputer/puter.js';
puter.ai.chat("Explain quantum computing in simple terms", {
model: "liquid/lfm-2.5-1.2b-instruct:free"
}).then(response => {
document.body.innerHTML = response.message.content;
});
<html>
<body>
<script src="https://js.puter.com/v2/"></script>
<script>
puter.ai.chat("Explain quantum computing in simple terms", {
model: "liquid/lfm-2.5-1.2b-instruct:free"
}).then(response => {
document.body.innerHTML = response.message.content;
});
</script>
</body>
</html>
# pip install openai
from openai import OpenAI
client = OpenAI(
base_url="https://api.puter.com/puterai/openai/v1/",
api_key="YOUR_PUTER_AUTH_TOKEN",
)
response = client.chat.completions.create(
model="liquid/lfm-2.5-1.2b-instruct:free",
messages=[
{"role": "user", "content": "Explain quantum computing in simple terms"}
],
)
print(response.choices[0].message.content)
curl https://api.puter.com/puterai/openai/v1/chat/completions \
-H "Content-Type: application/json" \
-H "Authorization: Bearer YOUR_PUTER_AUTH_TOKEN" \
-d '{
"model": "liquid/lfm-2.5-1.2b-instruct:free",
"messages": [
{"role": "user", "content": "Explain quantum computing in simple terms"}
]
}'
Model Card
LFM 2.5 1.2B Instruct is a compact instruction-tuned language model from Liquid AI, designed to deliver best-in-class performance at the 1-billion-parameter scale.
Trained on 28 trillion tokens with reinforcement learning, it achieves strong scores across knowledge (MMLU-Pro: 44.35), reasoning (GPQA: 38.89), and instruction following (IFEval: 86.23) — outperforming similarly sized models like Llama-3.2-1B and Gemma-3-1B on these benchmarks.
The model supports tool use, structured outputs, and function calling, making it a solid choice for lightweight agentic pipelines, chatbots, and latency-sensitive API integrations where cost and throughput matter most.
Context Window 33K
tokens
Max Output N/A
tokens
Input Cost $0
per million tokens
Output Cost $0
per million tokens
Release Date Jan 5, 2026
Model Playground
Try LFM2.5-1.2B-Instruct instantly in your browser.
This playground uses the Puter.js AI API — no API keys or setup required.
More AI Models From Liquid AI
LFM2-24B-A2B
LFM2 24B A2B is a sparse Mixture-of-Experts model from Liquid AI featuring a novel hybrid architecture that combines gated short convolution blocks with Grouped Query Attention in a 3:1 ratio, developed through hardware-in-the-loop architecture search. With 24 billion total parameters but only ~2 billion active per token, it delivers high throughput while outperforming larger MoE competitors like Qwen3-30B-A3B in throughput benchmarks. It supports 9 languages, a 32K context window, native function calling, and structured outputs. A strong API choice for high-volume multi-agent pipelines, RAG backends, and multilingual applications that demand low per-token cost alongside capable general reasoning.
ChatLFM2.5-1.2B-Thinking
LFM 2.5 1.2B Thinking is a compact reasoning model from Liquid AI that generates explicit chain-of-thought traces before producing answers, enabling more reliable performance on multi-step problems at the 1-billion-parameter scale. Compared to its instruct sibling, it shows major benchmark gains in math reasoning (MATH-500: 88 vs. 63), instruction following (Multi-IF: 69 vs. 61), and tool use (BFCLv3: 57 vs. 49). It matches or exceeds Qwen3-1.7B on most reasoning benchmarks despite having 40% fewer parameters. Well-suited for API use cases involving agentic tool calling, math, and code — anywhere a reasoning trace meaningfully improves answer quality.
Frequently Asked Questions
You can access LFM2.5-1.2B-Instruct by Liquid AI through Puter.js AI API. Include the library in your web app or Node.js project and start making calls with just a few lines of JavaScript — no backend and no configuration required. You can also use it with Python or cURL via Puter's OpenAI-compatible API.
Yes, it is free if you're using it through Puter.js. With the User-Pays Model, you can add LFM2.5-1.2B-Instruct to your app at no cost — your users pay for their own AI usage directly, making it completely free for you as a developer.
| Price per 1M tokens | |
|---|---|
| Input | $0 |
| Output | $0 |
LFM2.5-1.2B-Instruct was created by Liquid AI and released on Jan 5, 2026.
LFM2.5-1.2B-Instruct supports a context window of 33K tokens. For reference, that is roughly equivalent to 66 pages of text.
Yes — the LFM2.5-1.2B-Instruct API works with any JavaScript framework, Node.js, or plain HTML through Puter.js. Just include the library and start building. See the documentation for more details.
Get started with Puter.js
Add LFM2.5-1.2B-Instruct to your app without worrying about API keys or setup.
Read the Docs View Tutorials